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Information Flow Audit for PaaS Clouds

Authors: Thomas F. J.-M. Pasquier; Jatinder Singh; Jean Bacon; David M. Eyers;

Information Flow Audit for PaaS Clouds

Abstract

With the rapid increase in uptake of cloud services, issues of data management are becoming increasingly prominent. There is a clear, outstanding need for the ability for specified policy to control and track data as it flows throughout cloud infrastructure, to ensure that those responsible for data are meeting their obligations. This paper introduces Information Flow Audit, an approach for tracking information flows within cloud infrastructure. This builds upon CamFlow (Cambridge Flow Control Architecture), a prototype implementation of our model for data-centric security in PaaS clouds. CamFlow enforces Information Flow Control policy both intra-machine at the kernel-level, and inter-machine, on message exchange. Here we demonstrate how CamFlow can be extended to provide data-centric audit logs akin to provenance metadata in a format in which analyses can easily be automated through the use of standard graph processing tools. This allows detailed understanding of the overall system. Combining a continuously enforced data-centric security mechanism with meaningful audit empowers tenants and providers to both meet and demonstrate compliance with their data management obligations.

Countries
United Kingdom, United States, United Kingdom
Related Organizations
Keywords

4606 Distributed Computing and Systems Software, 46 Information and Computing Sciences, Privacy, Information Flow Control, Provenance, Security, 4604 Cybersecurity and Privacy, Information Flow Audit, Cloud, 004

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    20
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
20
Top 10%
Top 10%
Top 10%
Green